AStrion strategy: from acquisition to diagnosis. Application to wind turbine monitoring

Transcription

1 DOI: /isi XXX AUTOMATED CM AStrio strategy: from acquisitio to diagosis. Applicatio to wid turbie moitorig Z-Y Li, T Gerber, M Firla, P Bellemai, N Marti ad C Mailhes This paper proposes a automatic procedure for coditio moitorig. It presets a valuable tool for the maiteace of expesive ad spread systems, such as wid turbie farms. Thaks to data-drive sigal processig algorithms, the proposed solutio is fully automatic for the user. The paper briefly describes all the steps of the processig, from preprocessig of the acquired sigal to iterpretatio of the geerated results. It starts with a agular resamplig method with speed measuremet correctio. The comes a data validatio step, i both the time/agular ad frequecy/order domais. After the preprocessig, the spectral compoets of the aalysed sigal are idetified ad classified ito several classes, from sie wave to arrowbad compoets. This spectral peak detectio ad classificatio allows the harmoic ad side-bad series to be extracted, which may be part of the sigal spectral cotet. Moreover, the detected spectral patters are associated with the characteristic frequecies of the ivestigated system. Based o the detected side-bad series, the full-bad demodulatio is performed. At each step, the diagosis features are computed ad dyamically tracked, sigal by sigal. Fially, system health idicators are proposed to coclude the coditio of the ivestigated system. All the steps metioed create a self-sufficiet tool for a robust diagosis of mechaical faults. The paper presets the performace of the proposed method o real-world sigals from a wid turbie drivetrai. 1. Itroductio Coditio moitorig systems (CMS) are widely-used predictive maiteace tools that aim to diagose the health status of a system. This helps to reduce the operatig costs by detectig abormalities i the state of the ivestigated system. CMS are especially adapted to the maiteace of complicated mechaical systems, which are difficult to maitai by huma labour or which are located i remote areas hardly accessible by techicias. Wid turbies are typical examples of such systems ad CMS have achieved tremedous success i their maiteace [1,2]. The diagosis i a CMS is based o the aalysis of relevat sigals acquired from the moitored mechaical system. I geeral, the CMS ca be categorised ito two types. The first is systemdrive ad depeds o health idicators defied o the moitored kiematics compoets [3,4]. Therefore, the cofiguratio of the CMS is a delicate ad labour-demadig task, which cosiderably affects the accuracy of the diagosis. Moreover, every time a part of the moitored system is chaged, the CMS has to be recofigured. The secod type, amely the data-drive CMS, avoids these drawbacks by automatically deducig idicators from the sigals without a priori kowledge of the moitored system. Therefore, the complexity of the system cofiguratio is reduced to a miimum. AStrio is desiged to be the core vibratio aalysis compoet of a data-drive CMS. Aother compaio three-phase electrical sigature aalysis system [11] ca ru i parallel to automatically detect electrical faults. AStrio is a spectrum aalyser able to automatically detect ad track relevat fault features thaks to the richess of the iformatio extracted from the spectrum of the vibratio sigal. Istead of beig cofigured by experts, the cofiguratio of AStrio is achieved either by automatic data validatio or by decisio-makig algorithms of the method itself. The spectrum ivestigatio, the feature calculatio, the kiematic associatio ad the time-trackig of the features are automatically accomplished tasks. This makes AStrio perfectly suitable to be embedded i a wid turbie CMS, sice it is fully fuctioal without ay itervetio by the user. Aother key iterest of AStrio is its capability to extract a high quatity of iformatio from the spectrum. Not oly focused o the amplitude variatio o some particular kiematic frequecies, the spectrum ispectio is performed over the etire frequecy spa. All the harmoic series ad side-bad series are ivestigated i a exhaustive way idepedet of the system kiematics ad it is therefore advatageous i the ispectio of complex mechaical systems ad highly adaptive to a chage of the kiematic cofiguratio of the system. The features deduced from the harmoic series ad the demodulatio of the side-bad series are highly reliable ad idicative of the faults, which helps to detect faults at a early stage. The diagosis of faults requires the cotiuous acquisitio of the vibratio sigals ad the time trackig of the specific fault features of the sigals at differet time stamps. I the AStrio methods, some prior works [5,6,8] focused maily o the aalysis of a sigle sigal, while others focused o the time-trackig of the features [7]. I this paper, we will summarise the methodologies of the etire AStrio architecture, icludig both types of method. Through the demostratio of results ad applicatios, we will oly focus o the time-trackig of the features ad the cotiuous-time surveillace. Hereiafter, the steps ad the sigal processig methodologies Paper preseted at CM 2015 / MFPT 2015, the Twelfth Iteratioal Coferece o Coditio Moitorig ad Machiery Failure Prevetio Techologies, Oxford, UK, Jue 2015 Zhog-Yag Li, Timothée Gerber, Marci Firla, Pascal Bellemai ad Nadie Marti are with the Uiversité Greoble Alpes, GIPSA-Lab, F Greoble, Frace ad CNRS, GIPSA-Lab, F Greoble, Frace. firstame.lastame@gipsa-lab.greoble-ip.fr Corie Mailhes is with IRIT/ENSEEIHT/TéSA, Uiversity of Toulouse, Frace. corie.mailhes@eseeiht.fr Isight Vol 57 No 8 August

2 of AStrio are briefly preseted i Sectio 2. I Sectio 3, the results o real-world sigals are preseted to demostrate the validity of AStrio. Coclusios are draw i Sectio AStrio methodologies The AStrio methodologies cosist of a set of modules of two types. The first type processes a idividual vibratio sigal ad deduces scalar features as the descriptio of the sigal. The secod type is a time-trackig module, which serves to automatically coect the sets of scalar features calculated at each time istat. 2.1 Sigle-sigal processig modules Give the th vibratio sigal s i vector form: s = s 1,s 2,,s k,,s N s... (1) where k is the sample idex ad N s represets the umber of samples of each sigal, to deal with the o-statioarity issue, the sigal is firstly trasposed ito the order domai by a agular resamplig module called AStrio-A (A for Agular resamplig) [9] accordig to the availability of the phase marker measuremet. I the resampled sigal, the o-statioarity caused by the variatio of the rotatioal speed ca be reduced, sice the samplig is adusted to the agular positio of the rotatig part. I the followig step, either o the origial time domai sigal or o the resampled order domai sigal, a data-validatio module called AStrio-D (D for Data validatio) performs a pre-aalysis of the sigal to reveal the essetial properties, such as the acquisitio validity, the periodicity, the o-statioarity ad the oise level. The ext step is AStrio-I (I for peak Idetificatio), which fids the peaks i the spectral domai [5]. Due to the complexity of the real-world sigals, the spectral cotet related to the uderlyig sigal is distiguished from the oise spectrum usig a statistical test based o the properties of the spectrum estimator. The detected peaks are the classified to iterpret the uderlyig characteristics, such as oise, sie waves, arrowbad sigals, etc. The etire procedure is called a cycle. Sice the defiitio of a perfect spectral estimator i terms of performace is impossible, a multi-cycle strategy is proposed to apply a spectral aalysis procedure with two or five differet spectral estimators to take advatage of their differet stregths. The spectral estimators ad their parameters are chose accordig to the prior data validatio step. After all the cycles, a fusio operatio merges the results i the differet cycles ad creates a uique spectral idetity card for each detected spectral peak, cotaiig properties such as the amplitude, a i, the frequecy, v i, ad the associated ucertaity, ε i. i is the idex of the peak ad i N p, with N p the total umber of peaks detected i the sigal s. The ext module, called AStrio-H, searches the harmoic series ad side-bad series i the list of detected peaks [6]. Due to the ucertaity about the exact peak frequecy, the search for harmoics is made by iterval itersectio. Therefore, a peak is cosidered as the rth harmoic of aother peak i if the followig iterval itersectio is ot empty: v ε 2 ;v + ε h 2 r v + ε i i 2 ;r v + ε i i 2 /0 Each detected harmoic series has a idetity card, deoted as: where v { } 1,N H H = v,ε, E is the fudametal frequecy, ε... (2) is the ucertaity iterval aroud v, E is the eergy of the series ad N H is the total umber of harmoic series detected i the sigal s. The side-bad series, whose carrier frequecy belogs to at least oe harmoic series, ca be foud usig a similar iterval itersectio method. A specific idetity card is also defied for each side-bad series idetified: { } 1,N M M = v,δ,ε... (3) where v is the carrier frequecy, Δ is the modulatio frequecy, ε is the ucertaity about Δ ad N M is the total umber of sidebad series detected i sigal s. I the ext module, AStrio-K (K for Kiematics) [8], the harmoic series ad side-bad series are associated with the characteristic frequecies (or orders) of the moitored system. The cocered system kiematics, icludig the gear mesh frequecy (GMF), the ball pass frequecy of the ier rig (BPFI) ad the ball pass frequecy of the outer rig (BPFO), the fudametal trai frequecy (FTF) ad the double ball spi frequecy (BSF2), are cofigured usig the kiematic geometry. The kiematic associatio is carried out over the frequecy of each harmoic order ad side-bad order i all the harmoic ad side-bad series. The module is optioal ad is skipped if the kiematic iformatio is abset. The followig aalysis ad trackig will cocer both the associated ad o-associated series. The detected side-bads are the demodulated to calculate the modulatio fuctios i a module called AStrio-M (M for side-bad demodulatio) [8]. With the demodulatio bad defied by the prior AStrio-H module, the sigal is filtered aroud each side-bad rage to keep a sigle modulated compoet. The, a averaged sigal is calculated from the filtered sigal usig time sychroous averagig. Based o this averaged sigal, the amplitude ad the frequecy modulatio fuctios are calculated usig the Hilbert trasform. Eight features are added to the idetity card of each side-bad series: the average value, the peak-to-peak magitude, the modulatio idex ad the kurtosis of the amplitude ad frequecy modulatio fuctios, respectively. 2.2 Time-trackig ad surveillace module Fially, the harmoic series ad the side-bad series obtaied from all the sigals {s } are tracked i time by a module called AStrio-S (S for Surveillace) [7]. The trackig of the harmoic series takes ito accout the fudametal frequecy: if the fudametal frequecies of two harmoic series obtaied at two cosecutive time istats, ad + 1, fall ito a small frequecy/order eighbourhood, they are tracked i time ad cosidered as the evolutio of oe harmoic series. The peaks iside the series are automatically tracked accordig to their rak i the series. Note that if the harmoic series or the side-bad series tracked disappears betwee istats 1 ad 2, the traectory will be cosidered as hiberatig durig the time iterval [ 1, 2 ]. The trackig of the side-bad series is performed i a similar way; however, two parameters should be take ito accout: the carrier frequecy ad the modulatio frequecy. Sice the carrier frequecies ca be tracked a priori durig the trackig of the harmoic series, the peaks of the modulatio series, which have the same carrier frequecy, ca be tracked automatically accordig to the modulatio frequecies. The architecture of the AStrio software is summarised i Figure 1. I AStrio, the algorithms of each module are either cofigured by the module itself, such as AStrio-A, AStrio-D ad AStrio-S, 2 Isight Vol 57 No 8 August 2015

3 Figure 1. The modular architecture of AStrio or by the output of the prior modules, such as AStrio-I ad AStrio-M. I the case of abormalities of the acquired sigal, for example the variable shaft speed, the software is able to make the sigal statioary by covertig it i the agle domai. If the sigal is iappropriate for the spectrum aalysis, AStrio-D will alert the followig modules so that the sigal ca be discarded. Eve if a sigal is abadoed, AStrio-S is still able to label it as a sleep state ad proceed the traectory trackig i the correct way. 3. Applicatio o real-world sigals I this sectio, we focus o the applicatio of the etire AStrio software o real-world sigals to demostrate its ability i fault diagosis. Two sets of sigals are cosidered. The first came from a test-rig, where a degradatio test was desiged to produce a mechaical fault of a desired type o a desired mechaical compoet. This example aims to validate the proposed algorithms o a statioary operatioal coditio. The secod set of sigals was acquired from a wid turbie, where the presece of mechaical faults was ukow. This applicatio demostrates the applicability of AStrio i real-world situatios, where the operatig coditio is variable ad ukow. 3.1 Applicatio o the test-rig sigals The test-rig is a experimetal platform desiged o behalf of the KAStrio proect ad istalled i CETIM. It is dedicated to simulatig the deterioratio of a wid turbie drivetrai. The system was desiged o a smaller scale (10 kw) ad is drive by a motor istead of wid blades. A geared motor geerates the mai shaft rotatio (aroud 20 r/mi). A multiplier icreases the rotatioal speed with a ratio of 100:1, so that the geerator operates at aroud 2000 r/mi. As show i Figure 2, accelerometers ad phase markers allow for the exhaustive moitorig of the rig compoets, such as the mai bearig ad the gearbox. Figure 2. The test-rig. The mai bearig is marked by a orage ellipsis ad the three accelerometer directios are symbolised by the gree arrows I this paper, we focus o the fault detectio of the mai bearig by the accelerometer of the (+y) directio. 19 sigals were extracted durig 190 h of operatio (from h to h), whe the mai bearig was highly deteriorated i order to totally stop the ormal operatio i the ed. The bearig was fially disassembled ad the flakig was foud to be distributed o the etire ier rig. Each vibratio sigal was measured durig 150 s, sampled at 39,062.5 Hz uder a costat rotatioal speed ad load. AStrio was applied to the 19 sigals with all the modules except the agular resamplig, sice the rotatioal speed was kow to be costat. Amog these sigals, the 14th sigal, at h of operatio, was corrupted due to the existece of a spike of times the average amplitude [9]. The first two sigals, captured at h ad h of operatio, were cofirmed to be ivalid sice the sesor was discoected. The other 16 sigals were correctly acquired. Figure 3 shows the umber of peaks, harmoic series ad side-bad series detected o the 19 sigals. Figure 3. Results of the detectio of peaks, harmoic series ad side-bad series o the 19 sigals of accelerometer (+y), mouted o the mai bearig of the test-rig from to operatig hours: (a) umber of peaks detected; ad (b) umber of harmoic ad side-bad series detected Without the eed for ay pre-cofiguratio, AStrio detected oly 899 peaks i the ivalid 14th sigal, while about 51,000 to 61,000 peaks were detected i the other 16 sigals. The sigificat drop of the umber idicates the abormality of the 14th sigal. Note that prior to the peak detectio, the abormality ca be clearly detected i the data validatio module usig the o-statioarity rate [9]. The umber of peaks detected o the first two ivalid sigals is almost the same as the valid sigals, but there are almost o harmoic series ad side-bads, sice there was oly oise ad a few high-frequecy resoaces. Therefore, they had o ifluece i the feature trackig. I real-world applicatios, the sesor discoectio caot be reported by techicias i real time, while AStrio wisely treated them as ull acquisitios without ay spectral iformatio. They could also be detected durig the data validatio step by their very low sigal-to-oise ratios. Based o the valid sigals, the harmoic series associated with the BPFI of the mai bearig is of special iterest, sice the disassembly of the mai bearig cofirmed that the fault was a wide-spread flakig o the ier rig [10]. AStrio successfully detected the harmoic series associated with the bearig BPFI. Figure 4 shows two features calculated from the detected harmoic series. I Figure 4, a harmoic series has bee detected sice h. While the damage was gettig stroger, the umber of harmoics icreased ad the fudametal frequecy slightly decreased. The Isight Vol 57 No 8 August

4 empty area iside the curve correspods to the faulty measuremet that the time-trackig algorithm automatically skipped ad labelled as a sleep state. I [7], the authors demostrated that the same fault could also be detected by the eergy of the harmoic series. Moreover, sice the fault produced a modulatio at the shaft rotatio frequecy, the existece of the side-bad series with the carrier is equal to the BPFI (3.45 Hz), while the modulatio frequecy is equal to the shaft speed (0.333 Hz) ad is a direct idicator of the fault. AStrio was ot oly able to detect such sidebad series but was also able to demodulate it to compute the sidebad features, as show i Figure 5. Figure 4. Evolutio of (a) the umber of peaks ad (b) the fudametal frequecy of the harmoic series represetig the BPFI of the test-rig mai bearig Figure 6. (a) The geographical locatio of the wid turbie WT6 ad (b) the accelerometers A5 ad A6 istalled, respectively, at the frot ad the rear ed of the geerator Figure 5. Evolutio of the shaft speed (0.333 Hz) modulatios aroud the BPFI (3.45 Hz) carrier frequecy: (a) average of the amplitude modulatio fuctio; (b) average of the frequecy modulatio fuctio The sigals are of 10 s, sampled at 25,000 Hz, captured from 20 December 2014 to 7 Jauary 2015 with the shaft rotatig at 1600 r/mi to 1800 r/mi, as show i Figure 7. The time axis of Figure 5 is zoomed aroud the time istats where the fault ca be foud. The fault-related side-bad series was detected at the same time (129.2 operatig hours) as the appearace of the harmoic series of the BPFI of the rollig elemet bearig. The detectio by AStrio is five hours earlier tha usig the arrowbad root mea square (RMS), detected from 134 h [10]. Note that these treds help to track the severity of the distributio of the fault sice the rise of the average amplitude idicates the icreasig eergy of the fault-related side-bad. Other side-bad features calculated i AStrio [8] ca reveal the same fault. The fault detectio was achieved by explorig the etire frequecy bad. Istead of oly focusig o a preset characteristic fault frequecy as may system-drive methods do, AStrio looks for fault idicators by itself. It is capable of detectig other types of fault of other mechaical parts i the same way. 3.2 Applicatio o the Valorem wid turbie sigals I this sectio, the applicatio of AStrio o the vibratio sigals of a real-world wid turbie i the cotext of the KAStrio proect is preseted. The sigals, provided courtesy of Valorem, Frace, were captured by the same type of accelerometers mouted o the same wid turbie, as show i Figure 6. Figure 7. Evolutio of the mea rotatioal speed: (a) accelerometer A5; (b) accelerometer A6 35 sigals were selected o accelerometer A5 while 77 sigals were selected o accelerometer A6. To deal with the varyig rotatioal speed i the suveillace, the agular resamplig was carried out o all sigals before calculatig the spectra. As a result, the resampled sigals had sigificatly lower o-statioarity tha the o-resampled oes [9] ad the umber of peaks detected from the spectra of the resampled sigals was always higher tha 1600, as show i Figure 8. These peaks gave birth to 22 harmoic traectories o the sigals of A5 ad 35 harmoic traectories o the sigals of A6, which were automatically idetified, tracked ad associated with the kiematic iformatio. Amog all the harmoic series, the oe of order 1 was directly associated with the rotatio of 4 Isight Vol 57 No 8 August 2015

5 the shaft, as show i Figure 9. The harmoic series were tracked from the 6th sigal ad the 10th sigal, respectively, to the ed o A5 ad A6. Cosiderig the variatio of the rotatioal speed ad evirometal coditios, the idetificatio ad the trackig of the harmoic series are very robust. The robustess is a essetial cocer for logterm surveillace, because the CMS has to assure the cotiuous detectio ad moitorig of the kiematic frequecies to avoid missig the fault features, which ca appear at ay time. Figure 8. Evolutio of the umber of detected peaks for both accelerometers: (a) accelerometer A5; (b) accelerometer A6 Figure 9. Evolutio of the umber of peaks i the harmoic series associated with the shaft speed: (a) accelerometer A5; (b) accelerometer A6 Note that o side-bads related to ay faults were foud o each accelerometer ad therefore o alarms were raised. Meawhile, wid turbie experts have cofirmed that the moitored mechaical compoet was workig uder ormal operatioal coditios without defect. The absece of false alarms i this case shows the good reliability of AStrio. 3.3 Applicatio o the sigals of a aoymous wid turbie We hereby preset aother applicatio of AStrio o 54 vibratio sigals acquired over 11 moths o the gearbox of a aoymous wid turbie. The sigals are all trasformed i the agle domai by AStrio-A ad each of them is of about 300 revolutios (300,000 poits) with a rotatioal speed of 1500 r/mi. A fault i the gearbox was cofirmed later ad the gearbox was replaced oe moth after the acquisitio of the 54th sigal. Figure 10 presets the fault diagosis result of AStrio ad the arrowbad RMS. I AStrio, the gearbox fault was clearly idicated by a sigificat icrease of the frequecy modulatio idex from the 39th sigal, while the widely-used arrowbad RMS is ot idicative of the fault at all. Moreover, i AStrio, the same fault ca be clearly see ad, also from the o-statioary rate, the umber of fault-related side-bads ad their eergy. They are ot illustrated due to the limited umber of pages. Figure 10. Diagosis of the aoymous wid turbie gearbox: (a) frequecy modulatio idex obtaied i AStrio by demodulatig the side-bad series aroud the secod harmoic of GMF modulated by shaft speed; ad (b) arrowbad RMS computed with a badwidth of three side-bads o both sides of the carrier frequecy 4. Coclusios I this paper, we itroduced AStrio, a automatic spectrum aalyser dedicated to a wid turbie CMS. The algorithms ad the fuctio modules of AStrio are recalled. The applicatio o sigals from a test-rig validates the ability of AStrio to detect a bearig fault thaks to its automatic spectral aalysis algorithms. The results o real-world wid turbie sigals demostrate the reliability ad the robustess i log-term ad cotiuous surveillace tasks. AStrio is data-drive ad idepedet of ay a priori assumptio about the ature of the sigal. The exhaustive exploratio of the spectral cotet esures the capability of detectig a large variety of faults without maual ispectio. It is a valuable feature for a log-term automatic surveillace. Secodly, thaks to the robust ad reliable spectrum aalysis modules i AStrio, the fault idicators are calculated usig the properties of the methods themselves istead of maually chose thresholds. Its first beefit is to liberate the users from the delicate ad timecosumig task of pre-cofiguratio. The secod beefit is the Isight Vol 57 No 8 August

6 adaptability. I the preseted results, sigals from totally differet sesors, or eve differet mechaical systems, were all processed by the same software without ay recofiguratio. I practice, AStrio ca be applied o a arbitrary vibratio sesor. I future work, the alarm-raisig mechaism of some commo fault types will be proposed ad the false alarm rates will be evaluated as a idex of reliability or cofidece. Secodly, AStrio has to process a lot of peaks whe the sigals cotai a large umber of samples, while it has to face the accuracy degradatio of the spectral aalysis of short sigals. I terms of computatio efficiecy, the algorithm will cotiue to be optimised i order to fit the processig of both short sigals ad very log sigals. CM2015/MFPT2015, Oxford, UK, N Bédoui ad S Sieg-Zieba, Edurace testig o a wid turbie test-rig: a focus o slow rotatig bearig moitorig, I: CM2015/MFPT2015, Oxford, UK, G Cablea, P Grao, C Béreguer ad P Bellemai, Olie coditio moitorig of wid turbies through three-phase electrical sigature aalysis, I: CM2015/MFPT2015, Oxford, UK, Ackowledgemets The authors would like express their sicere appreciatio to CETIM for sharig the data of the test-rig, ad to VALEMO ad EC-Systems for providig the sigals of the real-world wid turbies. This research is part of the KAStrio proect ( gipsa-lab.fr/proet/kastrion/), which has bee supported by KIC IoEergy. KIC IoEergy is a compay supported by the Europea Istitute of Iovatio ad Techology (EIT) ad has the missio of deliverig commercial products ad services, ew busiesses, iovators ad etrepreeurs i the field of sustaiable eergy through the itegratio of higher educatio, research, etrepreeurs ad busiess compaies. This work has bee supported by the Frech Research Natioal Agecy (ANR) through the EITE programme (proect KAStrio ANR-12-EITE ). Refereces 1. B Lu, Y Li, X Wu ad Z Yag, A review of recet advaces i wid turbie coditio moitorig ad fault diagosis, Power Electroics ad Machies i Wid Applicatios 2009, PEMWA 2009, IEEE, P F G Márquez, A M Tobias, M J P Pérez ad M Papaelias, Coditio moitorig of wid turbies: techiques ad methods, Reewable Eergy, Vol 46, pp , X Gog ad W Qiao, Bearig fault diagosis for directdrive wid turbies via curret demodulated sigals, IEEE Trasactios o Idustrial Electroics, Vol 60, No 8, pp , D He, R Li ad J Zhu, Plastic bearig fault diagosis based o a two-step data miig approach, IEEE Trasactios o Idustrial Electroics, Vol 60, No 8, pp , C Mailhes, N Marti, K Sahli ad G Leeue, Coditio moitorig usig automatic spectral aalysis, I: Structural Health Moitorig, Spai, T Gerber, N Marti ad C Mailhes, Idetificatio of harmoics ad side-bads i a fiite set of spectral compoets, I: CM2013/MFPT2013, Kraków, Polad, T Gerber, N Marti ad C Mailhes, Moitorig based o time-frequecy trackig of estimated harmoic series ad modulatio side-bads, I: 4th Iteratioal Coferece o Coditio Moitorig of Machiery i No-Statioary Operatios (CMMNO 2014), Lyo, Frace, 2014, 10 p. 8. M Firla, Z-Y Li, N Marti ad T Barszcz, Automatic ad fullbad demodulatio for fault detectio. Validatio o a wid turbie test-rig, I: 4th Iteratioal Coferece o Coditio Moitorig of Machiery i No-Statioary Operatios (CMMNO 2014), Lyo, Frace, G Sog, Z-Y Li, P Bellemai, N Marti ad C Mailhes, AStrio data validatio of o-statioary wid turbie sigals, I: 6 Isight Vol 57 No 8 August 2015